در Coursera

در دانشگاه کاشان شماره ثبت 56db170dea30d

در دانشگاه کاشان شماره ثبت 56db173fcfea3

در سازمان نظام صنفی رایانه‌ای کشور با امتیاز 3

مدرس مدعو، مدیر گروه

در موسسه آموزش عالی علامه نائینی

مدرس و مدیر گروه کارشناسی ارشد مهندسی کامپیوتر گرایش نرم‌افزار

• پیوند

مدرس مدعو

در موسسه آموزش عالی نقش جهان

• پیوند

مدرس مدعو

در دانشگاه آزاد اسلامی واحد نجف آباد

تدریس درس مبانی کامپیوتر و برنامه سازی در گروه عمران

• پیوند

مدرس

در سیتکو (SITCO)

مدرس دوره C# مربوط به دوره NIIT

• پیوند

مدرس مدعو

در دانشگاه آزاد اسلامی واحد لنجان

• پیوند

مدرس مدعو

در دانشگاه پیام نور واحد علویجه

• پیوند

مدیر فناوری اطلاعات و ارتباطات (IT)

در موسسه کاریابی کارمند

• پیوند

مدرس مدعو

در دانشگاه پیام نور واحد خمینی شهر

• پیوند

محقق، تحلیلگر، طراح، برنامه‌نویس و توسعه دهنده

در شرکت بازتاب

• پیوند

محقق، تحلیلگر، طراح، برنامه‌نویس و توسعه دهنده

در شرکت نوید ارتباطات صفاهان

• پیوند

مدرس مدعو

در موسسه آموزش عالی بنیان

• پیوند

محقق، تحلیلگر، طراح، برنامه‌نویس و توسعه دهنده

در سامان انرژی

• پیوند

مدرس مدعو

در دانشگاه جامع علمی کاربردی مرکز علویجه

• پیوند

مدرس مدعو

در دانشگاه جامع علمی کاربردی مرکز تیران و کرون

• پیوند

برنامه نویس، پشتیبان

در آزمایشگاه تشخیص طبی مهدیه

• پیوند

روش‌های محاسبه نمادی ( 19/20 ) در دانشگاه کاشان (دکتری)

آزمون نرم‌افزار ( 18.5/20 ) در دانشگاه کاشان (دکتری)

طراحی نرم‌افزارهای مطمئن ( 20/20 ) در دانشگاه آزاد اسلامی واحد نجف آباد (کارشناسی ارشد)

پایگاه داده پیشرفته ( 18.5/20 ) در دانشگاه آزاد اسلامی واحد نجف آباد (کارشناسی ارشد)

مباحث پیشرفته در مهندسی نرم‌افزار ( 18/20 ) در دانشگاه آزاد اسلامی واحد نجف آباد (کارشناسی ارشد)

الگوریتم‌های موازی ( 18/20 ) در دانشگاه آزاد اسلامی واحد نجف آباد (کارشناسی ارشد)

مدلسازی و ارزیابی سیستم‌های کامپیوتری ( 20/20 ) در دانشگاه آزاد اسلامی واحد نجف آباد (کارشناسی ارشد)

سمینار ( 20/20 ) در دانشگاه آزاد اسلامی واحد نجف آباد (کارشناسی ارشد)

سیستم‌های عامل پیشرفته ( 17.5/20 ) در دانشگاه آزاد اسلامی واحد نجف آباد (کارشناسی ارشد)

سیستم‌های خبره و مهندسی دانش ( 16.40/20 ) در دانشگاه آزاد اسلامی واحد نجف آباد (کارشناسی ارشد)

مهندسی نرم‌افزار پیشرفته ( 15.75/20 ) در دانشگاه آزاد اسلامی واحد نجف آباد (کارشناسی ارشد)

روش تحقیق ( 16.5/20 ) در دانشگاه آزاد اسلامی واحد نجف آباد (کارشناسی ارشد)

پایان نامه ( 19.15/20 ) در دانشگاه آزاد اسلامی واحد نجف آباد (کارشناسی ارشد)

مجله،در International Journal of Computer Science and Network Security

Map-Reduce is often used in implementation of critical and important tasks such as analysis of the scientific data. However, evidences in the past indicate the presence of optional errors that can destroy the results of Map-Reduce. Of course, run times of Map-Reduce like Hadoop can tolerate crash errors, but do not tolerate arbitrary or Byzantine errors. Hence in this paper, at first, the Hadoop architecture in distributed system will be investigated and then Hadoop will be compared with Map-Reduce and finally the Map-Reduce fault tolerance will be investigated.

همکاران : آرمین کشکولی، بهزاد سلیمانی نیسیانی، مینا رهبری،

کنفرانس،در International Conference on Knowledge-Based Engineering and Innovation (KBEI)،2

Validation and verification of software or system specifications are crucial in reducing costs and proper software development. Software specifications are usually represented by semi-formal languages like UML. For verification of non-formal and semi-formal models, they should be first transformed into a formal language. The state chart is one of the well-known UML charts that describe the behavior of a system and used for modeling many systems such as resource managements and communications in networks or distributed systems. In this paper, we propose a method to automatically map a UML state chart to BIR language, which is designed for BOGOR model checking. The goal of the verification in this paper is to evaluate the deadlock property of this chart. The proposed method is evaluated by four case studies of ATM and Fax machine state charts and the model is verified regarding the existence of a deadlock. Results indicate that while the PAT verification tool cannot properly recognize deadlocks in a state chart, the proposed approach is capable of detecting such cases of a deadlock. (3) Automatic Verification of UML State Chart by BOGOR Model Checking Tool Automatic Formal Verification of Network and Distributed Systems.

همکاران : بهزاد سلیمانی نیسیانی، سید مرتضی بابامیر،

کنفرانس،در International Conference on Knowledge-Based Engineering and Innovation (KBEI)،2

Association Rule Mining is concerned with the search for relationships between item-sets based on co-occurrence of patterns. Since transactional databases are being updated all the time and there are always data being added or deleted, so Incremental Association Rule Mining is very important. Many methods have been presented so far for incremental frequent pattern mining, one of these methods is the frequent patterns mining base on the CAN tree (CANonical-order TREE). Related works on CAN tree, didn't discuss about extraction of frequent patterns from the tree and it has only been suggested that the mining method would be similar to FP-growth. In this paper, a new method is presented for mining CAN tree, and it is evaluated to show its improvement over the FP-growth method that mine FP tree. The evaluation results have demonstrated that performance of the presented algorithm is better than the FP-growth algorithm at high minimum support thresholds and for future work can try to improve it for lower minimum support threshold.

همکاران : معصومه سادات حسینی، محمد ندیمی شهرکی، بهزاد سلیمانی نیسیانی،

کنفرانس،در International Conference on Knowledge-Based Engineering and Innovation (KBEI)،2

UML is a standard modeling language in software engineering. Although this language is capable of describing and modeling different aspects of a problem, it cannot be used for verification of the obtained model. Formal languages can be utilized for this purpose to verify the model. In a previous study by the authors of this paper, Statecharts diagram has been mapped to the LOTOS formal language. However, not all possible structures and necessary relations like the condition and loop structures were mapped. In this paper, an improvement of the previous method is presented. Moreover, for verification of the presented mapping, the CADP toolbox has been used. To apply the proposed method in practice, a case study is presented, where the properties deadlock, live lock, unreachable states, and non-deterministic states are formally verified. The results of the model verification show that the evaluated Statecharts diagram has had deadlocks, but there have not been live locks, unreachable states, or non-deterministic states in it.

همکاران : محمد جوانی، بهزاد سلیمانی نیسیانی، سید مرتضی بابامیر،

کنفرانس،در International Conference on Knowledge-Based Engineering and Innovation (KBEI)،2

Recently, many companies in Iran use telemarketing to introduce their products. These companies need to detect their best target to following them over seasons and years for more sales. This paper introduces a simple and appropriate method to predict behavior of customers based on behavior of prior customers. First of all, a dataset of customer action should be made and then preprocessed to reduce its attribute and dimension. Then a neural network will be made based on selected features to predict sale behavior of customers. Finally an evolutionary algorithm like genetic can be used to find feature of customers who will buy products more. This method evaluated by Portuguese Bank Tele Marketing dataset. Results show it simply can find the best customers in this case study. It's highly recommended to companies use this method to reduce their marketing costs and have better performance.

همکاران : بهزاد سلیمانی نیسیانی، نسیم سلطانی، شیما قزلباش،

مجله،در Emerging Science Journal،2

Recommender systems are designed for offering products to the potential customers. Collaborative Filtering is known as a common way in Recommender systems which offers recommendations made by similar users in the case of entering time and previous transactions. Low accuracy of suggestions due to a database is one of the main concerns about collaborative filtering recommender systems. In this field, numerous researches have been done using associative rules for recommendation systems to improve accuracy but runtime of rule-based recommendation systems is high and cannot be used in the real world. So, many researchers suggest using evolutionary algorithms for finding relative best rules at runtime very fast. The present study investigated the works done for producing associative rules with higher speed and quality. In the first step Apriori-based algorithm will be introduced which is used for recommendation systems and then the Particle Swarm Optimization algorithm will be described and the issues of these 2 work will be discussed. Studying this research could help to know the issues in this research field and produce suggestions which have higher speed and quality.

همکاران : حسین حاتمی ورزنه، بهزاد سلیمانی نیسیانی، حسن ضیافت، نسیم سلطانی،